/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:14: NumbaWarning:
Compilation is falling back to object mode WITH looplifting enabled because Function "l2_norm" failed type inference due to: Invalid use of Function(<function norm at 0x7f884c0f4dd0>) with argument(s) of type(s): (axis=Literal[int](1), x=array(float32, 2d, A))
* parameterized
In definition 0:
TypeError: norm_impl() got an unexpected keyword argument 'x'
raised from /home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/typing/templates.py:475
In definition 1:
TypeError: norm_impl() got an unexpected keyword argument 'x'
raised from /home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/typing/templates.py:475
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: resolving callee type: Function(<function norm at 0x7f884c0f4dd0>)
[2] During: typing of call at /home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py (16)
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 16:
def l2_norm(in_matrix):
return np.linalg.norm(x=in_matrix, axis=1)
^
@jit(float32[:](float32[:, :]), nogil=True)
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:742: NumbaWarning: Function "l2_norm" was compiled in object mode without forceobj=True.
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 15:
@jit(float32[:](float32[:, :]), nogil=True)
def l2_norm(in_matrix):
^
self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:751: NumbaDeprecationWarning:
Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.
For more information visit http://numba.pydata.org/numba-doc/latest/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 15:
@jit(float32[:](float32[:, :]), nogil=True)
def l2_norm(in_matrix):
^
warnings.warn(errors.NumbaDeprecationWarning(msg, self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:14: NumbaWarning: Code running in object mode won't allow parallel execution despite nogil=True.
@jit(float32[:](float32[:, :]), nogil=True)
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:29: NumbaPerformanceWarning: np.dot() is faster on contiguous arrays, called on (array(float32, 1d, A), array(float32, 1d, A))
dist[i, j] = np.dot(m[i], n[j])
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:88: NumbaWarning:
Compilation is falling back to object mode WITH looplifting enabled because Function "find_mutual_nn" failed type inference due to: Untyped global name 'cKDTree': cannot determine Numba type of <class 'type'>
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 90:
def find_mutual_nn(data1, data2, k1, k2, n_jobs):
k_index_1 = cKDTree(data1).query(x=data2, k=k1, n_jobs=n_jobs)[1]
^
@jit((float32[:, :], float32[:, :], int8, int8, int8))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:88: NumbaWarning:
Compilation is falling back to object mode WITHOUT looplifting enabled because Function "find_mutual_nn" failed type inference due to: Untyped global name 'cKDTree': cannot determine Numba type of <class 'type'>
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 90:
def find_mutual_nn(data1, data2, k1, k2, n_jobs):
k_index_1 = cKDTree(data1).query(x=data2, k=k1, n_jobs=n_jobs)[1]
^
@jit((float32[:, :], float32[:, :], int8, int8, int8))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:742: NumbaWarning: Function "find_mutual_nn" was compiled in object mode without forceobj=True, but has lifted loops.
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 89:
@jit((float32[:, :], float32[:, :], int8, int8, int8))
def find_mutual_nn(data1, data2, k1, k2, n_jobs):
^
self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:751: NumbaDeprecationWarning:
Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.
For more information visit http://numba.pydata.org/numba-doc/latest/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 89:
@jit((float32[:, :], float32[:, :], int8, int8, int8))
def find_mutual_nn(data1, data2, k1, k2, n_jobs):
^
warnings.warn(errors.NumbaDeprecationWarning(msg, self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:102: NumbaWarning:
Compilation is falling back to object mode WITH looplifting enabled because Function "compute_correction" failed type inference due to: Invalid use of Function(<function unique at 0x7f884c078c20>) with argument(s) of type(s): (array(int32, 1d, A), return_counts=bool)
* parameterized
In definition 0:
TypeError: np_unique() got an unexpected keyword argument 'return_counts'
raised from /home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/typing/templates.py:475
In definition 1:
TypeError: np_unique() got an unexpected keyword argument 'return_counts'
raised from /home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/typing/templates.py:475
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: resolving callee type: Function(<function unique at 0x7f884c078c20>)
[2] During: typing of call at /home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py (105)
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 105:
def compute_correction(data1, data2, mnn1, mnn2, data2_or_raw2, sigma):
<source elided>
vect = data1[mnn1] - data2[mnn2]
mnn_index, mnn_count = np.unique(mnn2, return_counts=True)
^
@jit(float32[:, :](float32[:, :], float32[:, :], int32[:], int32[:], float32[:, :], float32))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:102: NumbaWarning:
Compilation is falling back to object mode WITHOUT looplifting enabled because Function "compute_correction" failed type inference due to: cannot determine Numba type of <class 'numba.dispatcher.LiftedLoop'>
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 107:
def compute_correction(data1, data2, mnn1, mnn2, data2_or_raw2, sigma):
<source elided>
vect_reduced = np.zeros((data2.shape[0], vect.shape[1]), dtype=np.float32)
for index, ve in zip(mnn2, vect):
^
@jit(float32[:, :](float32[:, :], float32[:, :], int32[:], int32[:], float32[:, :], float32))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:742: NumbaWarning: Function "compute_correction" was compiled in object mode without forceobj=True, but has lifted loops.
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 103:
@jit(float32[:, :](float32[:, :], float32[:, :], int32[:], int32[:], float32[:, :], float32))
def compute_correction(data1, data2, mnn1, mnn2, data2_or_raw2, sigma):
^
self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:751: NumbaDeprecationWarning:
Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.
For more information visit http://numba.pydata.org/numba-doc/latest/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 103:
@jit(float32[:, :](float32[:, :], float32[:, :], int32[:], int32[:], float32[:, :], float32))
def compute_correction(data1, data2, mnn1, mnn2, data2_or_raw2, sigma):
^
warnings.warn(errors.NumbaDeprecationWarning(msg, self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:199: NumbaWarning:
Compilation is falling back to object mode WITH looplifting enabled because Function "adjust_s_variance" failed type inference due to: Untyped global name 'sq_dist_to_line': cannot determine Numba type of <class 'numba.ir.UndefinedType'>
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 209:
def adjust_s_variance(data1, data2, curcell, curvect, sigma):
<source elided>
sameproj = np.dot(grad, samecell)
samedist = sq_dist_to_line(curcell, grad, samecell)
^
@jit(float32(float32[:, :], float32[:, :], float32[:], float32[:], float32), nogil=True)
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:199: NumbaWarning:
Compilation is falling back to object mode WITHOUT looplifting enabled because Function "adjust_s_variance" failed type inference due to: cannot determine Numba type of <class 'numba.dispatcher.LiftedLoop'>
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 207:
def adjust_s_variance(data1, data2, curcell, curvect, sigma):
<source elided>
totalprob2 = 0.
for samecell in data2:
^
@jit(float32(float32[:, :], float32[:, :], float32[:], float32[:], float32), nogil=True)
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:742: NumbaWarning: Function "adjust_s_variance" was compiled in object mode without forceobj=True, but has lifted loops.
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 200:
@jit(float32(float32[:, :], float32[:, :], float32[:], float32[:], float32), nogil=True)
def adjust_s_variance(data1, data2, curcell, curvect, sigma):
^
self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/numba/compiler.py:751: NumbaDeprecationWarning:
Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.
For more information visit http://numba.pydata.org/numba-doc/latest/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit
File "../../../../home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py", line 200:
@jit(float32(float32[:, :], float32[:, :], float32[:], float32[:], float32), nogil=True)
def adjust_s_variance(data1, data2, curcell, curvect, sigma):
^
warnings.warn(errors.NumbaDeprecationWarning(msg, self.func_ir.loc))
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:199: NumbaWarning: Code running in object mode won't allow parallel execution despite nogil=True.
@jit(float32(float32[:, :], float32[:, :], float32[:], float32[:], float32), nogil=True)
/home/lebrigand/.conda/envs/paget/lib/python3.7/site-packages/mnnpy/utils.py:238: NumbaPerformanceWarning: np.dot() is faster on contiguous arrays, called on (array(float32, 1d, C), array(float32, 1d, A))
scale = np.dot(working, grad)